Prattle is expanding beyond the world of Federal Reserve statements to cover earnings calls, the quarterly events that allow analysts to grill executives about the state of their businesses.

Research has shown that analysts and fund managers value the post-earnings-report conference call and other direct communication with executives, which is one of the key ways they build a picture of a company and generate earnings forecasts. Executives also deem earnings to be one of the most important areas of communication with the investing community, and they rehearse carefully for each call

People speak in patterns

The underlying principle of Prattle’s machine-learning algorithm is that “people speak in patterns,” and that those patterns are not random. “Rather, linguistic patterns link specifically to the conscious and subconscious thoughts of the communicator,” Prattle wrote in a white paper. “These patterns manifest in the language of a corporate executive like a poker player’s tell.”

Prattle

Prattle CEO Evan Schnidman.

Prattle’s algorithm seeks to link a company executive’s historical speech patterns with the performance of a company’s stock, then it scores the lexicon, including individual words, phrases, sentences and so on, by their past impact on the stock’s price.

“By controlling for common fundamental factors like peer-company performance, Prattle scores represent the price movement that can be directly tied to the sentiment expressed in corporate communications,” according to the white paper.

A Prattle sentiment score is the expected 10-day cumulative abnormal return (CAR) resulting from the language of a company conference call.

For example, Intel Corp.’s conference call late on April 27 after the release of first-quarter results received a Prattle score of -1.74, which indicates the language of the call should statistically lead to a 1.74% decline from the stock’s benchmark level.

That might help explain why Intel’s stock
INTC, -0.72%
slumped 3.4% the next session, even though the chip maker had reported earnings that were well above expectations and revenue that was just a bit shy of the consensus forecast.

FactSet, MarketWatch

PepsiCo Inc., meanwhile, reported quarterly results before the Oct. 4 opening bell — earnings that handily beat expectations, while revenue was just slightly below the mark, similar to Intel’s results.

But unlike Intel’s call, the PepsiCo conference call was scored a 1.03 and was ranked in the 84th percentile, which means it contained more positive language than some 84% of past earnings calls. The stock
PEP, -0.46%
initially fell as much as 2.7%, before bouncing sharply to close up 0.2%. It then rallied 1% in the next session.

FactSet, MarketWatch

While the one-off scores can be helpful in predicting short-term stock directions, reading the Prattle scores in a time series can also serve as a leading indicator of company and stock performance.

For example, Nike Inc.’s first-quarter call after the Sept. 26 closing bell was scored 3.07, which is fairly bullish on an absolute basis, and was ranked in the 92nd percentile. The stock
NKE, +1.06%
ran up as much as 3.2% in after-hours trade, after a big earnings beat and a very slight revenue miss.

In the next session, however, the stock dropped 1.9%, then fell another 2.3% through Tuesday to close at a four-month low. The Dow Jones Industrial Average
DJIA, -0.35%
climbed 2.2% to a record close over the same time span. Although the Prattle score was strongly positive, it was down from a 3.23 score after the fourth-quarter conference call on June 29 and a 3.35 score after the third-quarter call on March 21.

Prattle Equities Analytics

“The Nike signal demonstrated that despite weaker-than-expected revenue, the management team was optimistic about the outlook, likely because [earnings per share exceeded] estimates,” said Schnidman. “Nevertheless, the signal was not as positive as other recent Nike earnings calls, which helps explain why, after an initial pop, [the] stock price has declined a bit since the earnings call.”

Hatched at Harvard

The idea for Prattle was hatched while Schnidman was a graduate student at Harvard University, using automated analysis to study Fed communication during the 2008 financial crisis. It was a critical period for the Fed as it moved away from the cryptic communication style of Alan Greenspan to the more open approach of Ben Bernanke, which featured press conferences beginning in 2011.

Schnidman saw a way to cut through the clutter and sell forecasts to investment firms based on the text analyses. Today, Prattle analyzes the communication of 20 central banks around the world. It scored a success in September 2015, when it correctly forecast that the Fed would hold interest rates steady, even though many in the market expected a rate hike.

In 2016, Prattle raised a $3.3 million seed round led by GCM Grosvenor, with participation from New Enterprise Associates, Correlation Ventures, Plug and Play Ventures, Neotribe Ventures, and a group of prominent Silicon Valley and Wall Street angel investors.

In May, the company launched a beta version of its new Prattle Equities Analytics product. The product was officially launched in September and quantifies communications from nearly 3,000 publicly traded companies in the U.S. The third-quarter earnings season, which kicks of on Thursday with the first big bank reports, is the company’s first full earnings-season effort.

Prattle Equities Analytics is already part of the Nasdaq Analytics Hub, a platform that offers buy-side investors signals derived from structured and unstructured data. The hub is aimed at asset and hedge-fund managers, algorithmic traders, and active managers, who are increasingly keen on any alternative data sets that might give them a trading edge.

Prattle now has 30 employees based in Boston, St. Louis and New York. Its client base includes large asset managers, hedge funds and international investment banks.

The company’s bigger vision is to build a corporate intelligence database, building on regulatory actions. The company is aiming to expand into other developed markets.

Intraday Data provided by SIX Financial Information and subject to terms of use. Historical and current end-of-day data provided by SIX Financial Information. All quotes are in local exchange time. Real-time last sale data for U.S. stock quotes reflect trades reported through Nasdaq only. Intraday data delayed at least 15 minutes or per exchange requirements.